Time series data aggregation query method, device, computer equipment and readable medium

Abstract

The invention provides a time series data aggregate query method and apparatus, a computer device and a readable medium. The method comprises the steps of receiving an aggregate query request of timeseries data of a user, wherein the aggregate query request carries an aggregate function, time windows and a time range; according to the time windows of an internal layer aggregate function of the aggregate function, the time range, and corresponding relationships between time of the time series data and storage nodes of the time series data, establishing two-dimensional fragmentation informationon a time dimension and a storage dimension in the time range, controlling the storage nodes corresponding to the time windows to locally execute related operations of the internal layer aggregate function according to the internal layer aggregate function and multiple storage node identifiers corresponding to the time windows identified in the two-dimensional fragmentation information, and returning operation results; and according to the received operation results corresponding to the time windows in the time range and the aggregate function, generating an aggregate query result. Accordingto the technical scheme, the aggregate query efficiency can be effectively improved.

Description

[0001] 【Technical field】 [0002] The present invention relates to the technical field of computer applications, in particular to a time series data aggregation query method, device, computer equipment and readable medium. [0003] 【Background technique】 [0004] In the Internet of Things scenario, time-series data will continue to be generated in large quantities. Time-series databases often use multi-node fragmentation storage. These historical time-series data can be used for effective monitoring and trend prediction. A typical example is to query the hourly data of the latest month. The average temperature, so the time series database needs to be able to support efficient aggregation operation query, referred to as aggregation query. [0005] When the existing time-series data is aggregated and queried, after receiving the query request from the user, it parses the query request and builds a logical query tree, analyzes and optimizes the logical query tree, and finally the ...

AI Technical Summary

Problems solved by technology

[0006] In the above-mentioned aggregation query processing adopted by the prior art, each data storage node needs to transmit a large amount of original time series data to the computing node, resulting in a great pressure on the input / output (I / O) of the system; and the computing node needs to execute all Aggregation operations, the calculation pressure is too large; this leads to a large delay in the entire aggregation query, and low efficiency of the aggregation query

Images